

Wan 3.0 and MiniMax H3 side by side: specs, capabilities, parameters, and live pricing from the EmpirioLabs catalog.
Wan 3.0 from Alibaba Cloud and MiniMax H3 from MiniMax are both in the Video Generation category, available through the EmpirioLabs API.
| Spec | Wan 3.0 | MiniMax H3 |
|---|---|---|
| Model ID | wan-3-0 | minimax-h3 |
| Author | Alibaba Cloud | MiniMax |
| Released | Aug 6, 2026 | Jul 31, 2026 |
| Input | Text Image Video Audio | Text Image Video Audio |
| Output | Video | Video |
| Region | Singapore | Singapore |
| Endpoints | POST /v1/videos/generations | POST /v1/videos/generations |
| Capabilities |
Live rates from the EmpirioLabs catalog for both models. Each rate card always matches what the API charges.
Request parameters each model lists on EmpirioLabs, with the allowed values or range where one applies. A dash marks a parameter the model does not list.
| Parameter | Wan 3.0 | MiniMax H3 |
|---|---|---|
| prompt | string | string |
| model_tier | standard, prime Default: standard | - |
| mode | auto, t2v, i2v, r2v Default: auto | auto, t2v, i2v, flf, r2v, regenerate Default: auto |
| resolution | 480p, 720p, 1080p Default: 1080p | 768p, 2k Default: 768p |
| duration | 2 to 30 Default: 5 | 4 to 15 Default: 6 |
| aspect_ratio | adaptive, 16:9, 9:16, 1:1, 4:3, 3:4 Default: adaptive | adaptive, 21:9, 16:9, 4:3, 1:1, 3:4, 9:16 Default: adaptive |
| image | string | string |
| video | string | string |
| seed | 0 to 2147483647 | - |
| audio | boolean Default: true | string |
| watermark | boolean Default: false | boolean Default: false |
| prompt_extend | boolean Default: true | - |
| link | string | - |
| file_url | string | - |
| last_frame | - | string |
| base_video | - | string |
Generation can take several minutes on the standard tier; the prime tier is significantly faster end to end. Modes are auto-detected from attachments, or override with the mode parameter. The model_tier parameter picks standard or prime; each tier bills at its own per-second rate.
MiniMax H3 generates 4 to 15 second clips at 24 fps in 768p or 2K, each with a native stereo audio track.
Set enhance_prompt to true and the model first rewrites your brief into a full prompt, adding shot-by-shot structure, camera moves, lighting and a soundscape, then renders from that. Any reference media you attach informs the expansion. It adds a per-token charge on top of the per-second video cost, and is skipped for regeneration because that path reproduces the original request.
Wan 3.0 runs through POST /v1/videos/generations. The request returns a job_id right away; poll GET /v1/jobs/{job_id} until the job completes and read the output URLs from the result. Both models are called through the same endpoint. Set model to wan-3-0 or minimax-h3. Get an API key from the EmpirioLabs dashboard.
curl https://api.empiriolabs.ai/v1/videos/generations \
-H "Authorization: Bearer $EMPIRIOLABS_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"model": "wan-3-0",
"prompt": "Describe what you want Wan 3.0 to generate."
}'Prompt tests and comparison runs that cover both models.
Wan 3.0 is the newer release (Aug 6, 2026); MiniMax H3 was released on Jul 31, 2026. Capabilities listed only for Wan 3.0: text to video, reference to video, audio sync, character consistency. Capabilities listed only for MiniMax H3: video generation, audio out, audio in, multimodal. The specs, rate cards, and parameters on this page come from the live EmpirioLabs catalog.
Wan 3.0 is the newer release (Aug 6, 2026); MiniMax H3 was released on Jul 31, 2026.
The two models are priced on different units or tiers, so compare the live rate cards on this page. They always match what the API charges.
Yes. Both models use POST /v1/videos/generations with the same EmpirioLabs API key, so most integrations switch by changing the model value. Check the parameters table on this page first if you rely on a model-specific parameter.
Yes. Open each model in the EmpirioLabs playground and run the same prompt on both, with the parameters the API exposes.
Check out our pricing or reach out if you want your own model deployed on our stack.